Triple
T11191295
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Benjamin Hawkins |
E264805
|
entity |
| Predicate | hadPartner |
P97763
|
FINISHED |
| Object | Creek woman (common-law wife) |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Creek woman (common-law wife) | Statement: [Benjamin Hawkins, hadPartner, Creek woman (common-law wife)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadPartner Context triple: [Benjamin Hawkins, hadPartner, Creek woman (common-law wife)]
-
A.
hasAffairWith
Indicates that one entity is engaged in a secret or illicit romantic or sexual relationship with another entity, typically outside a committed partnership.
-
B.
marriedBefore
Indicates that one entity entered into a marriage at an earlier time than the other entity.
-
C.
hadGender
Indicates that an entity possessed a specific gender.
-
D.
hasConcubineFrom
Indicates that a person has a concubine whose origin or affiliation is from a specified place or source.
-
E.
hasSex
Indicates that one entity engages in sexual activity with another entity.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d6aa9eb9248190b20211772621b4bc |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8af18e4819091811bca657c9cb0 |
completed | April 9, 2026, 5:58 p.m. |
| PD | Predicate disambiguation | batch_69d75cf4461c8190af84060f7db83211 |
completed | April 9, 2026, 8:01 a.m. |
| PDg | Predicate description generation | batch_69d77062271c8190b63da714ab5beff9 |
completed | April 9, 2026, 9:24 a.m. |
Created at: April 8, 2026, 9:29 p.m.